IJBTT

Comparative Analysis of Traditional and AI-Driven Data Governance: A Systematic Review and Future Directions in IT
	© 2024 by IJCTT Journal
	Volume-72 Issue-11
	Year of Publication : 2024
	Authors : Kishore Babu Tenneti, Susmitha Pandula, Sravya Pandula
	DOI :  10.14445/22312803/IJCTT-V72I11P116

How to Cite?

Kishore Babu Tenneti, Susmitha Pandula, Sravya Pandula, "Comparative Analysis of Traditional and AI-Driven Data Governance: A Systematic Review and Future Directions in IT," International Journal of Computer Trends and Technology, vol. 72, no. 11, pp. 150-158, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I11P116

Abstract
In this context, this paper aims to offer a systematic review of data governance with a specific focus on the traditional approach to data management and the AI-based approach. The second paper reviews advancements in data governance frameworks, concurring with the importance of stringent control where data volume and variability are rising. The literature review also discusses core concepts tied to conventional governance frameworks, focusing on how AI revolutionizes data handling. By comparing the cases, the study points to how AI offers fresh opportunities regarding data governance responsibilities, productivity, and issues such as real-time data management. Finally, the review brings out the key conclusions on the subject matter, culminating in exploring how AI integrates reliability, conformity, and the lifelong management of data for organizations.

Keywords
Data protection and AI, Data governance, Artificial Intelligence in data governance, Traditional data governance, AI systems, and Data Governance.

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